def report_CEA_CBA(multi_cohort_outcomes_SOC, multi_cohort_outcomes_NSB):
""" performs cost-effectiveness and cost-benefit analyses
:param multi_cohort_outcomes_SOC: outcomes of a multi-cohort simulated under SOC diagnostic
:param multi_cohort_outcomes_NSB: outcomes of a multi-cohort simulated under NSB diagnostic
"""
# define two strategies
SOC_diagnostic_strategy = Econ.Strategy(
name='SOC Diagnostic',
cost_obs=multi_cohort_outcomes_SOC.meanCosts,
effect_obs=multi_cohort_outcomes_SOC.totalYLL,
color='green'
)
NSB_diagnostic_strategy = Econ.Strategy(
name='NSB Diagnostic',
cost_obs=multi_cohort_outcomes_NSB.meanCosts,
effect_obs=multi_cohort_outcomes_NSB.totalYLL,
color='blue'
)
# do CEA
CEA = Econ.CEA(
strategies=[SOC_diagnostic_strategy, NSB_diagnostic_strategy],
if_paired=True,
health_measure='d'
)
# show the cost-effectiveness plane
show_ce_figure(CEA=CEA)
# report the CE table
CEA.build_CE_table(
interval_type='p', # prediction intervals
alpha=D.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2)
# CBA
NBA = Econ.CBA(
strategies=[SOC_diagnostic_strategy, NSB_diagnostic_strategy],
if_paired=True,
health_measure='d'
)
# show the net monetary benefit figure
NBA.graph_incremental_NMBs(
min_wtp=0,
max_wtp=50000,
title='Cost-Benefit Analysis',
x_label='Willingness-To-Pay for One Additional QALY ($)',
y_label='Incremental Net Monetary Benefit ($)',
interval_type='p',
show_legend=True,
figure_size=(6, 5)
)
def report_CEA_CBA(multi_trees_P, multi_trees_N):
""" performs cost-effectiveness and cost-benefit analyses
:param multi_cohort_outcomes_mono: outcomes of a multi-cohort simulated under mono therapy
:param multi_cohort_outcomes_combo: outcomes of a multi-cohort simulated under combination therapy
"""
# define two strategies
Palivizumab_therapy_strategy = Econ.Strategy(
name='Palivizumab Therapy',
cost_obs=multi_trees_P.PCosts,
effect_obs=multi_trees_P.PQALYs,
color='green'
)
No_prophylaxis_strategy = Econ.Strategy(
name='No Prophylaxis',
cost_obs=multi_trees_N.NCosts,
effect_obs=multi_trees_N.NQALYs,
color='blue'
)
# do CEA
CEA = Econ.CEA(
strategies=[Palivizumab_therapy_strategy, No_prophylaxis_strategy],
if_paired=True
)
# show the cost-effectiveness plane
show_ce_figure(CEA=CEA)
# report the CE table
CEA.build_CE_table(
interval_type='p', # prediction intervals
alpha=D.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2)
# CBA
NBA = Econ.CBA(
strategies=[Palivizumab_therapy_strategy, No_prophylaxis_strategy],
if_paired=True
)
# show the net monetary benefit figure
NBA.graph_incremental_NMBs(
min_wtp=0,
max_wtp=5000000,
title='Cost-Benefit Analysis',
x_label='Willingness-To-Pay for One Additional QALY ($)',
y_label='Incremental Net Monetary Benefit ($)',
interval_type='p',
show_legend=True,
figure_size=(6, 5)
)
def report_CEA_CBA(multi_cohort_outcomes_no, multi_cohort_outcomes_asp):
# define two strategies
no_therapy_strategy = Econ.Strategy(
name='Mono Therapy',
cost_obs=multi_cohort_outcomes_no.meanCosts,
effect_obs=multi_cohort_outcomes_asp.meanQALYs,
color='green'
)
asp_therapy_strategy = Econ.Strategy(
name='Combination Therapy',
cost_obs=multi_cohort_outcomes_asp.meanCosts,
effect_obs=multi_cohort_outcomes_no.meanQALYs,
color='blue'
)
# do CEA
CEA = Econ.CEA(
strategies=[no_therapy_strategy, asp_therapy_strategy],
if_paired=True
)
# show the cost-effectiveness plane
show_ce_figure(CEA=CEA)
# report the CE table
CEA.build_CE_table(
interval_type='p', # prediction intervals
alpha=D.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2)
# CBA
NBA = Econ.CBA(
strategies=[no_therapy_strategy, asp_therapy_strategy],
if_paired=True
)
# show the net monetary benefit figure
NBA.graph_incremental_NMBs(
min_wtp=0,
max_wtp=50000,
title='Cost-Benefit Analysis',
x_label='Willingness-To-Pay for One Additional QALY ($)',
y_label='Incremental Net Monetary Benefit ($)',
interval_type='p',
show_legend=True,
figure_size=(6, 5)
)
def report_CEA_CBA(sim_outcomes_amino, sim_outcomes_immuno):
""" performs cost-effectiveness and cost-benefit analyses
:param sim_outcomes_amino: outcomes of a cohort simulated under aminosalicylate therapy
:param sim_outcomes_immuno: outcomes of a cohort simulated under immunosuppresive therapy
"""
# define two strategies
amino_therapy_strategy = Econ.Strategy(
name='Aminosalicylate Therapy',
cost_obs=sim_outcomes_amino.costs,
effect_obs=sim_outcomes_amino.numPatientsAlive,
color='green')
immuno_therapy_strategy = Econ.Strategy(
name='Immunosuppresive Therapy',
cost_obs=sim_outcomes_immuno.costs,
effect_obs=sim_outcomes_immuno.numPatientsAlive,
color='blue')
# do CEA
CEA = Econ.CEA(
strategies=[amino_therapy_strategy, immuno_therapy_strategy],
if_paired=False)
# show the cost-effectiveness plane
show_ce_figure(CEA=CEA)
# report the CE table
CEA.build_CE_table(interval_type='c',
alpha=D.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2)
# CBA
NBA = Econ.CBA(
strategies=[amino_therapy_strategy, immuno_therapy_strategy],
if_paired=False)
# show the net monetary benefit figure
NBA.graph_incremental_NMBs(
min_wtp=0,
max_wtp=50000,
title='Cost-Benefit Analysis',
x_label='Willingness-to-pay for one additional QALY ($)',
y_label='Incremental Net Monetary Benefit ($)',
interval_type='c',
show_legend=True,
figure_size=(6, 5))
def report_CEA_CBA(sim_outcomes_SOC, sim_outcomes_NSB):
""" performs cost-effectiveness and cost-benefit analyses
:param sim_outcomes_mono: outcomes of a cohort simulated under mono therapy
:param sim_outcomes_combo: outcomes of a cohort simulated under combination therapy
"""
# define two strategies
SOC_diagnostic_strategy = Econ.Strategy(
name='SOC Diagnostic',
cost_obs=sim_outcomes_SOC.costsPresenting,
effect_obs=sim_outcomes_SOC.listYLLPresenting,
color='green')
sim_outcomes_NSB = Econ.Strategy(
name='NSB Diagnostic',
cost_obs=sim_outcomes_NSB.costsPresenting,
effect_obs=sim_outcomes_NSB.listYLLPresenting,
color='blue')
# do CEA
CEA = Econ.CEA(strategies=[SOC_diagnostic_strategy, sim_outcomes_NSB],
if_paired=False,
health_measure='d')
# show the cost-effectiveness plane
show_ce_figure(CEA=CEA)
# report the CE table
CEA.build_CE_table(interval_type='c',
alpha=D.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2)
# CBA
NBA = Econ.CBA(strategies=[SOC_diagnostic_strategy, sim_outcomes_NSB],
if_paired=False)
# show the net monetary benefit figure
NBA.graph_incremental_NMBs(
min_wtp=0,
max_wtp=50000,
title='Cost-Benefit Analysis',
x_label='Willingness-to-pay for one additional YLL ($)',
y_label='Incremental Net Monetary Benefit ($)',
interval_type='c',
show_legend=True,
figure_size=(6, 5))
def report_CEA_CBA(sim_outcomes_none, sim_outcomes_treat):
""" performs cost-effectiveness and cost-benefit analyses
:param sim_outcomes_mono: outcomes of a cohort simulated under mono therapy
:param sim_outcomes_combo: outcomes of a cohort simulated under combination therapy
"""
# define two strategies
none_therapy_strategy = Econ.Strategy(
name='No Therapy',
cost_obs=sim_outcomes_none.costs,
effect_obs=sim_outcomes_none.nTotalCured,
color='green')
treat_therapy_strategy = Econ.Strategy(
name='Intervention to Increase Adherence',
cost_obs=sim_outcomes_treat.costs,
effect_obs=sim_outcomes_treat.nTotalCured,
color='blue')
# do CEA
CEA = Econ.CEA(strategies=[none_therapy_strategy, treat_therapy_strategy],
if_paired=False)
# show the cost-effectiveness plane
show_ce_figure(CEA=CEA)
# report the CE table
CEA.build_CE_table(interval_type='c',
alpha=D.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2)
# CBA
NBA = Econ.CBA(strategies=[none_therapy_strategy, treat_therapy_strategy],
if_paired=False)
# show the net monetary benefit figure
NBA.graph_incremental_NMBs(
min_wtp=0,
max_wtp=1000,
title='Cost-Benefit Analysis',
x_label='Willingness-to-pay for one additional patient cured ($)',
y_label='Incremental Net Monetary Benefit ($)',
interval_type='c',
show_legend=True,
figure_size=(6, 5))
def report_CEA_CBA(sim_outcomes_NO, sim_outcomes_ASP):
# define two strategies
NO_therapy_strategy = Econ.Strategy(name='No Therapy',
cost_obs=sim_outcomes_NO.costs,
effect_obs=sim_outcomes_NO.utilities,
color='green')
ASP_therapy_strategy = Econ.Strategy(name='Aspirin Therapy',
cost_obs=sim_outcomes_ASP.costs,
effect_obs=sim_outcomes_ASP.utilities,
color='blue')
# do CEA
CEA = Econ.CEA(strategies=[NO_therapy_strategy, ASP_therapy_strategy],
if_paired=False)
# show the cost-effectiveness plane
show_ce_figure(CEA=CEA)
# report the CE table
CEA.build_CE_table(interval_type='c',
alpha=D.ALPHA,
cost_digits=0,
effect_digits=2,
icer_digits=2)
# CBA
NBA = Econ.CBA(strategies=[NO_therapy_strategy, ASP_therapy_strategy],
if_paired=False)
# show the net monetary benefit figure
NBA.graph_incremental_NMBs(
min_wtp=0,
max_wtp=100000,
title='Cost-Benefit Analysis',
x_label='Willingness-to-pay for one additional QALY ($)',
y_label='Incremental Net Monetary Benefit ($)',
interval_type='c',
show_legend=True,
figure_size=(6, 5))
from SimPy import EconEvalClasses as ce
import numpy as np
np.random.seed(573)
s_center = np.array([[10000, 0.2], [20000, 0.3], [50000, 0.35]])
s0 = ce.Strategy("s1", s_center[0, 0] + np.random.normal(0, 1000, 10),
s_center[0, 1] + np.random.normal(0, 0.01, 10))
s1 = ce.Strategy("s1", s_center[1, 0] + np.random.normal(0, 1000, 10),
s_center[1, 1] + np.random.normal(0, 0.01, 10))
s2 = ce.Strategy("s2", s_center[2, 0] + np.random.normal(0, 1000, 10),
s_center[2, 1] + np.random.normal(0, 0.05, 10))
nmb_paired = ce.CBA([s0, s1, s2],
if_paired=True) # list of frontier strategies as input
nmb_indp = ce.CBA([s0, s1, s2],
if_paired=False) # list of frontier strategies as input
# Try NMB_Lines figure - paired CI
nmb_paired.graph_deltaNMB_lines(0,
50000,
"deltaNMB lines for paired CI",
"wtp values",
"NMB values",
interval_type=ce.Interval.CONFIDENCE,
show_legend=True,
figure_size=6)
# Try NMB_Lines figure - paired PI
nmb_paired.graph_deltaNMB_lines(0,
50000,